Secure Multi-party Computation Analysis
Secure Multi-Party Computation Analysis is a formal academic concept referring to a computational framework within encrypted data analysis that enables multiple parties to jointly evaluate a function over their private inputs while preserving data confidentiality, distinguished by its reliance on cryptographic protocols that ensure no party learns more than the output, thus enabling privacy-preserving collaborative analysis without trusted third parties.
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2017–2026
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Adaptively secure multi-party computation
Ran Canetti, Uri Feige, Oded Goldreich et al. · 1996 · 553 citations · Full text
Secure Multi-Party Computation: Theory, practice and applications
Chuan Zhao, Shengnan Zhao, Minghao Zhao et al. · Information Sciences · 2018 · 484 citations
Xiao Wang, Hubert Chan, Elaine Shi · 2015 · 229 citations
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Cornell University
Ithaca, United States
3 h-index
3 publications
289 citations
Tsinghua University
Beijing, China
3 h-index
4 publications
598 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
2 h-index
2 publications
261 citations
Cybernetica (Estonia)
Tallinn, Estonia
2 h-index
4 publications
252 citations
Oregon State University
Corvallis, United States
2 h-index
3 publications
531 citations
University of Tartu
Tartu, Estonia
2 h-index
2 publications
126 citations
University of Maryland, College Park
College Park, United States
2 h-index
2 publications
261 citations

Beijing University of Posts and Telecommunications
Beijing, China
2 h-index
3 publications
45 citations
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2 publications · 522 citations
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1 publications · 104 citations
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1 publications · 56 citations
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Repository · 1 publications · 15 citations
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